Markerless Motion Capture to Quantify Functional Performance in Neurodegeneration: Systematic Review.
Parkinson's disease
body tracking
clinical decision making
decision
decision making
dementia
markerless motion capture
mild cognitive impairment
mobility
monitoring
motion
motion analysis
movement
movement analysis
neurodegeneration
neurodegenerative
neurodegenerative disease
systematic review
tool
tracking
Journal
JMIR aging
ISSN: 2561-7605
Titre abrégé: JMIR Aging
Pays: Canada
ID NLM: 101740387
Informations de publication
Date de publication:
06 Aug 2024
06 Aug 2024
Historique:
received:
08
09
2023
accepted:
15
07
2024
revised:
22
03
2024
medline:
6
8
2024
pubmed:
6
8
2024
entrez:
6
8
2024
Statut:
epublish
Résumé
Markerless motion capture (MMC) uses video cameras or depth sensors for full body tracking and presents a promising approach for objectively and unobtrusively monitoring functional performance within community settings, to aid clinical decision-making in neurodegenerative diseases such as dementia. The primary objective of this systematic review was to investigate the application of MMC using full-body tracking, to quantify functional performance in people with dementia, mild cognitive impairment, and Parkinson disease. A systematic search of the Embase, MEDLINE, CINAHL, and Scopus databases was conducted between November 2022 and February 2023, which yielded a total of 1595 results. The inclusion criteria were MMC and full-body tracking. A total of 157 studies were included for full-text screening, out of which 26 eligible studies that met the selection criteria were included in the review. . Primarily, the selected studies focused on gait analysis (n=24), while other functional tasks, such as sit to stand (n=5) and stepping in place (n=1), were also explored. However, activities of daily living were not evaluated in any of the included studies. MMC models varied across the studies, encompassing depth cameras (n=18) versus standard video cameras (n=5) or mobile phone cameras (n=2) with postprocessing using deep learning models. However, only 6 studies conducted rigorous comparisons with established gold-standard motion capture models. Despite its potential as an effective tool for analyzing movement and posture in individuals with dementia, mild cognitive impairment, and Parkinson disease, further research is required to establish the clinical usefulness of MMC in quantifying mobility and functional performance in the real world.
Sections du résumé
BACKGROUND
BACKGROUND
Markerless motion capture (MMC) uses video cameras or depth sensors for full body tracking and presents a promising approach for objectively and unobtrusively monitoring functional performance within community settings, to aid clinical decision-making in neurodegenerative diseases such as dementia.
OBJECTIVE
OBJECTIVE
The primary objective of this systematic review was to investigate the application of MMC using full-body tracking, to quantify functional performance in people with dementia, mild cognitive impairment, and Parkinson disease.
METHODS
METHODS
A systematic search of the Embase, MEDLINE, CINAHL, and Scopus databases was conducted between November 2022 and February 2023, which yielded a total of 1595 results. The inclusion criteria were MMC and full-body tracking. A total of 157 studies were included for full-text screening, out of which 26 eligible studies that met the selection criteria were included in the review. .
RESULTS
RESULTS
Primarily, the selected studies focused on gait analysis (n=24), while other functional tasks, such as sit to stand (n=5) and stepping in place (n=1), were also explored. However, activities of daily living were not evaluated in any of the included studies. MMC models varied across the studies, encompassing depth cameras (n=18) versus standard video cameras (n=5) or mobile phone cameras (n=2) with postprocessing using deep learning models. However, only 6 studies conducted rigorous comparisons with established gold-standard motion capture models.
CONCLUSIONS
CONCLUSIONS
Despite its potential as an effective tool for analyzing movement and posture in individuals with dementia, mild cognitive impairment, and Parkinson disease, further research is required to establish the clinical usefulness of MMC in quantifying mobility and functional performance in the real world.
Identifiants
pubmed: 39106477
pii: v7i1e52582
doi: 10.2196/52582
doi:
Types de publication
Systematic Review
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
e52582Informations de copyright
©Julian Jeyasingh-Jacob, Mark Crook-Rumsey, Harshvi Shah, Theresita Joseph, Subati Abulikemu, Sarah Daniels, David J Sharp, Shlomi Haar. Originally published in JMIR Aging (https://aging.jmir.org), 06.08.2024.